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体验新版 GitCode,发现更多精彩内容 >>
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40aee48a
编写于
9月 26, 2017
作者:
C
caoying03
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差异文件
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上级
3d77360b
变更
1
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Showing
1 changed file
with
14 addition
and
14 deletion
+14
-14
paddle/operators/softmax_with_cross_entropy_op.cc
paddle/operators/softmax_with_cross_entropy_op.cc
+14
-14
未找到文件。
paddle/operators/softmax_with_cross_entropy_op.cc
浏览文件 @
40aee48a
...
...
@@ -23,11 +23,6 @@ class SoftmaxWithCrossEntropyOpMaker
SoftmaxWithCrossEntropyOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddAttr
<
bool
>
(
"softLabel"
,
"(bool, default: false), A flag to indicate whether to interpretate "
"the given labels as soft labels."
)
.
SetDefault
(
false
);
AddInput
(
"Logits"
,
"(Tensor, default: Tensor<float>), The unscaled log probabilities "
"which is a 2-D tensor with shape [N x K]. N is the batch_size, "
...
...
@@ -49,6 +44,11 @@ class SoftmaxWithCrossEntropyOpMaker
AddOutput
(
"Loss"
,
"(Tensor, default: Tensor<float>), A 2-D tensor. The cross "
"entropy loss with shape [N x 1]."
);
AddAttr
<
bool
>
(
"softLabel"
,
"(bool, default: false), A flag to indicate whether to interpretate "
"the given labels as soft labels."
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
Cross entropy loss with softmax are used as the output layer extensively. This
operator computes the softmax normalized values for each row of the input
...
...
@@ -95,18 +95,18 @@ class SoftmaxWithCrossEntropyOp : public framework::OperatorWithKernel {
const
Tensor
*
logits
=
ctx
.
Input
<
Tensor
>
(
"Logits"
);
const
Tensor
*
labels
=
ctx
.
Input
<
Tensor
>
(
"Label"
);
PADDLE_ENFORCE
(
logits
->
dims
().
size
()
==
2UL
,
PADDLE_ENFORCE
_EQ
(
logits
->
dims
().
size
()
,
2UL
,
"The input of softmax_with_cross_entropy should be a 2-D tensor."
);
PADDLE_ENFORCE
(
ctx
.
Input
<
Tensor
>
(
"Label"
)
->
dims
().
size
()
==
2UL
,
"The labels should be a 2-D tensor."
);
PADDLE_ENFORCE
_EQ
(
ctx
.
Input
<
Tensor
>
(
"Label"
)
->
dims
().
size
(),
2UL
,
"The labels should be a 2-D tensor."
);
if
(
ctx
.
Attr
<
bool
>
(
"softLabel"
))
{
PADDLE_ENFORCE_EQ
(
logits
->
dims
()[
1
],
labels
->
dims
()[
1
],
"If Attr(softLabel) == true, the 2nd dimension of "
"Input(X) and Input(Label) should be equal."
);
}
else
{
PADDLE_ENFORCE_EQ
(
labels
->
dims
()[
1
],
1
,
PADDLE_ENFORCE_EQ
(
labels
->
dims
()[
1
],
1
UL
,
"If Attr(softLabel) == false, the 2nd dimension of "
"Input(Label) should be 1."
);
}
...
...
@@ -130,21 +130,21 @@ class SoftmaxWithCrossEntropyOpGrad : public framework::OperatorWithKernel {
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"Softmax"
),
"Input(Softmax) should be not null."
);
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"Label"
),
"Input(Lab
le
) should be not null."
);
"Input(Lab
el
) should be not null."
);
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
OutputVar
(
framework
::
GradVarName
(
"Logits"
)),
"Output(Logits@Grad) should be not null."
);
const
Tensor
*
softmax
=
ctx
.
Input
<
Tensor
>
(
"Softmax"
);
const
Tensor
*
labels
=
ctx
.
Input
<
Tensor
>
(
"Label"
);
PADDLE_ENFORCE
(
ctx
.
Input
<
Tensor
>
(
"Label"
)
->
dims
().
size
()
==
2UL
,
"The labels should be a 2-D tensor."
);
PADDLE_ENFORCE
_EQ
(
ctx
.
Input
<
Tensor
>
(
"Label"
)
->
dims
().
size
(),
2UL
,
"The labels should be a 2-D tensor."
);
if
(
ctx
.
Attr
<
bool
>
(
"softLabel"
))
{
PADDLE_ENFORCE_EQ
(
softmax
->
dims
()[
1
],
labels
->
dims
()[
1
],
"When Attr(softLabel) == true, the 2nd dimension of "
"Input(X) and Input(Label) should be equal."
);
}
else
{
PADDLE_ENFORCE_EQ
(
labels
->
dims
()[
1
],
1
,
PADDLE_ENFORCE_EQ
(
labels
->
dims
()[
1
],
1
UL
,
"When Attr(softLabel) == false, the 2nd dimension of "
"Input(Label) should be 1."
);
}
...
...
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